Decisions reduce sensitivity to subsequent information

Abstract

Behavioural studies over half a century indicate that making categorical choices alters beliefs about the state of the world. People seem biased to confirm previous choices, and to suppress contradicting information. These choice-dependent biases imply a fundamental bound of human rationality. However, it remains unclear whether these effects extend to lower level decisions, and only little is known about the computational mechanisms underlying them. Building on the framework of sequential-sampling models of decision-making, we developed novel psychophysical protocols that enable us to dissect quantitatively how choices affect the way decisionmakers accumulate additional noisy evidence. We find robust choice-induced biases in the accumulation of abstract numerical (experiment 1) and low-level perceptual (experiment 2) evidence. These biases deteriorate estimations of the mean value of the numerical sequence (experiment 1) and reduce the likelihood to revise decisions (experiment 2). Computational modelling reveals that choices trigger a reduction of sensitivity to subsequent evidence via multiplicative gain modulation, rather than shifting the decision variable towards the chosen alternative in an additive fashion. Our results thus show that categorical choices alter the evidence accumulation mechanism itself, rather than just its outcome, rendering the decision-maker less sensitive to new information.

Interacting with volatile environments stabilizes hidden-state inference and its brain signatures

“…Furthermore, participants showed no sign of leaky inference within each sequence, in either condition. The slower reversal learning in the outcome-based condition is also unlikely to arise from a biased, choice-supportive filtering of evidence described and reported across cognitive domains (Sharot et al, 2011;Bronfman et al, 2015;Lefebvre et al, 2017;Talluri et al, 2018;Yon et al, 2018). Indeed, the strength of conflicting evidence (inconsistent with beliefs) could be decoded with equal precision across conditions.…”

Choices Change the Temporal Weighting of Decision Evidence

“…These task designs have led us to two insights. First, the overall sensitivity to evidence following the intermittent choice is reduced in a non-selective ('global') fashion, a finding obtained in the domain of numerical decisions [35]. Second, sensitivity for information consistent with the binary choice is selectively enhanced, at the expense of less sensitivity for choiceinconsistent evidence, a choice-induced evidence re-weighting that produced a bias to confirm the initial choice and that was found for both perceptual and numerical decisions [38].…”

“…Recently developed task protocols provide new tools for assessing the impact of choices on the accumulation of subsequent decision evidence. These tasks prompt two successive judgments within the same trial: commonly a binary choice followed up by a continuous estimation [33][34][35][36][37][38] or a confidence [39,40] judgment. Specifically, some tasks prompt binary choice and estimation judgments sequentially, separated by a second evidence stream presented in between [35,39,40,38].…”

Agency, Teleological Control and Robust Causation

“…Research in psychology and behavioral neuroscience backs up these theoretical analyses, showing that we are more likely to be persuaded by evidence in the early stages of a decision than toward its end, when a stable decision‐state (and intention) is formed, as indicated by commitment biases (Bronfman et al. , Nickerson ). Nevertheless, too much stability corresponds to unwise stubbornness and achieving optimal action control performance involves a compromise between flexibility and stability…”